The invention relates to a method for identifying structural elements of a structural pattern, which is projected onto a scene, in camera images.
The invention furthermore relates to an apparatus for identifying structural elements of a structural pattern, which is projected onto a scene, in camera images, in particular for performing the above-mentioned method.
The invention additionally relates to the use of a previously mentioned method and/or a previously mentioned apparatus for monitoring, in particular securing, a danger zone, in particular a danger zone of a machine, such as a press or a robot.
In the context of the present invention, a scene is understood to mean in particular a three-dimensional danger zone that is monitored by the cameras. Moving objects, such as people, may be present in the scene. In the latter case in particular, cameras monitor the scene as to whether a person or a body part thereof is located in or approaches a dangerous proximity to a machine which operates in automated fashion.
In order to monitor danger zones, in particular danger zones of machines and industrial plants, it is known to use cameras, as is described in EP 2 133 619 A1. Here, a 3D security camera is disclosed, which has a first and a second image sensor, which can each generate image data of the spatial region. The 3D security camera operates together with a projector, which generates a structured illumination pattern in the scene, i.e. in the spatial region. According to the stereoscopy principle, an evaluation unit generates from the image data a depth map of the spatial region, which is monitored for inadmissible intrusions in the spatial region.
During the stereoscopic evaluation of image pairs of a stereo camera, measurement errors can occur due to low-contrast objects or repeating structures within the monitored spatial region. For this reason, as described in the aforementioned document, a structural pattern is projected into the field of vision of the cameras in order to improve the contrast in the camera images. It is advantageous here to use structural patterns in the form of periodic dot patterns, as are likewise already disclosed in the aforementioned document. Structural patterns in the form of dot patterns have the advantage over more complex structural patterns that they are sharply delineated and that less illumination energy is necessary for projecting them.
A projected structural pattern within the context of the present invention is an optical structural pattern, in other words a pattern which consists of light spots.
However, a problem arises when using dot patterns, in particular homogeneous dot patterns, as structural patterns in that erroneous assignments of dots in the camera images to the dots projected in the into the scene frequently occur. This is because the location of one projected structural element in the images of the cameras generally depends on the current distance of the projected structural element from the cameras and likewise on the geometry of the object onto which the structural element is projected. In other words, the location of a structural element in the camera images can vary in dependence on the distance and the object geometry, and can generally differ in the cameras.
An erroneous assignment of dots in the camera images to the dots projected onto the scene results in an erroneous determination of the distance from an object within the scene. An erroneous distance measurement in turn has the effect that dangerous situations can arise if, for example, an object which is located in the danger zone is deemed by the cameras to be outside the danger zone, or of insufficient availability, for example of a machine within the danger zone, if an object is located outside the danger zone, but is deemed by the cameras to be inside the danger zone due to an erroneous distance measurement, and the machine is therefore switched off.
A solution to the problem of the erroneous assignment of structural elements in the camera images to the structural elements projected onto the scene according to EP 2 019 281 A1 is that of projecting more complex structural patterns onto the scene that are, at least in partial regions, inhomogeneous, aperiodic and non-self-similar. However, the generation of such more complex structural patterns is disadvantageous in light of the high outlay in terms of apparatus, i.e. the complexity of the projector.
WO 2013/145665 A1 discloses an apparatus for three-dimensional measurement, which projects light lines from a projector onto a workpiece, wherein a stereo camera picks up an image of the workpiece onto which the light lines are projected. A control apparatus of the apparatus temporarily identifies a correspondence between a bright line in a first image of the picked-up stereo image and a light section plane, and projects the bright line onto the light section plane. The bright line, which is projected onto the light section plane, is projected onto a second image. The control apparatus calculates the degree of similarity between a bright line, which is projected onto the second image, and a bright line in the second image, and determines the result of the identified correspondence relationship between the projected bright line and the bright line in the second image.
US 2008/0201101 A1 discloses a handheld three-dimensional scanner for scanning and digitizing the surface geometry of items.
DE 20 2008 017 729 U1 discloses a 3D security camera for monitoring and securing a spatial region. The security camera has an illumination unit having at least one semiconductor light source. The semiconductor light source generates a high optical output of at least 10 W, which permits generation of a dense depth map for a reliable evaluation independent of fluctuations in the ambient light in the monitored spatial region.
DE 10 2004 020 419 B3 discloses an apparatus for measuring even strongly curved reflective surfaces. Patterns which are reflected at the surface are observed here and evaluated. The reflected patterns are observed from multiple directions. Evaluation is effected by determining those sites within the measurement space at which surface normals determined for the various observation directions have the lowest deviations with respect to one another.